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Face Relighting from a Single Image



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1968 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE VOL 31 NO 11 NOVEMBER 2009 Face Relighting from a Single Image under Arbitrary Unknown Lighting Conditions Yang Wang Member IEEE Lei Zhang Zicheng Liu Senior Member IEEE Gang Hua Member IEEE Zhen Wen Zhengyou Zhang Fellow IEEE and Dimitris Samaras Member IEEE Abstract In this paper we present a new method to modify the appearance of a face image by manipulating the illumination condition when the face geometry and albedo information is unknown This problem is particularly difficult when there is only a single image of the subject available Recent research demonstrates that the set of images of a convex Lambertian object obtained under a wide variety of lighting conditions can be approximated accurately by a low dimensional linear subspace using a spherical harmonic representation Moreover morphable models are statistical ensembles of facial properties such as shape and texture In this paper we integrate spherical harmonics into the morphable model framework by proposing a 3D spherical harmonic basis morphable model SHBMM The proposed method can represent a face under arbitrary unknown lighting and pose simply by three low dimensional vectors i e shape parameters spherical harmonic basis parameters and illumination coefficients which are called the SHBMM parameters However when the image was taken under an extreme lighting condition the approximation error can be large thus making it difficult to recover albedo information In order to address this problem we propose a subregion based framework that uses a Markov random field to model the statistical distribution and spatial coherence of face texture which makes our approach not only robust to extreme lighting conditions but also insensitive to partial occlusions The performance of our framework is demonstrated through various experimental results including the improved rates for face recognition under extreme lighting conditions Index Terms Face



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